Alumni of the Group Cybernetics Approach to Perception and Action
Alumni of the Group Motion Perception and Simulation
Project leader Motion Perception and Simulation research group
I am co-leading the research group. In this group, we are investigating the process of human self-motion perception and how this knowledge can be exploited in motion simulation. We do fundamental research into perceptual psychophysics and perceptual modelling, as well as more applied studies into motion cueing and control behavavior in simulation environments. For more details about our activities, please visit our .
I am also leading the research group. Within this group, we use the principles of cybernetics, control theory and system identification to further our understanding of human manual control. In particular, we investigate haptic support systems, neuromuscular identification methods and helicopter augmentation systems. For more details, please visit our .
I obtained my B.Sc. and M.Sc. in Aerospace Engineering from Delft University of Technology. Between 2010 and 2014, I have been working in a collaborative research project between Delft University of Technology and Max Planck Institute for Biological Cybernetics, resulting in a for my work on Biodynamic Feedthrough. Since April 2013, I work as project leader of the research group and since July 2015 as project leader of the research group. My research interstest include: motion perception, motion cueing, biodynamic interferences, neuromuscular modeling, and haptics. On these pages, you can find my and .
Scopus author ID:
WABS: Perception-based motion simulation
Duration: December 2011 - November 2014
Within the WABS project (Wahrnehmungsbasierte Bewegungssimulation) we developed a novel approach to motion cueing. Motion cueing is the process of converting a desired physical motion into motion simulator input commands. As a motion simulator is limited to move within a confined space, the desired physical motion can typically not be reproduced fully by the simulator. Successful simulation therefore requires motion cueing tricks, which are implemented in a so-called motion cueing algorithm (MCA).
Within the WABS project, we developed a perception-based motion cueing (PBMC) approach. A key difference with the traditional approaches to motion cueing is that PBMC operates by optimizing the simulator input commands based on the output of a model of human self-motion perception. This approach increases the realism and quality of motion simulations by exploiting the limitations and ambiguities of the human perceptual system.
I joined the WABS project in April 2013, in the role as project leader. Next to general management duties, I contributed to the PBMC algorithm development, experiment execution and the analysis of experimental results.
Figure 1: Schematic representation of the perception-based motion
cueing approach (PBMC) [Venrooij et al., DSC 2015 Europe].
myCopter: Enabling technologies for Personal Aerial Transporation Systems
Duration: January 2011 - December 2014
The existing problem of traffic congestion, combined with its anticipated growth, presents a major challenge for future societal mobility and economic growth. A promising solution that combines the best of air- and ground-based transportation is to establish a personal aerial transportation system (PATS) based on Personal Aerial Vehicles (PAVs). This presents new challenges with both technological and societal concerns. The myCopter project investigated the idea of a PATS based on small PAVs, for short distance commuting between home and the workplace. Such vehicles are expected to take off and land vertically, allowing their use in densely populated areas. The aim of myCopter was to determine the social and technical aspects needed to set up a transportation system based on PAVs in todays society.
The outcomes of this project provide a stepping stone for future endeavours aimed at moving personal transportation into the third dimension. The project has demonstrated that a PATS can become a reality, given appropriate technological advancements and socio-technological considerations.
I contributed to the myCopter project from January 2011 to June 2013 with my work on Biodynamic Feedthrough in PAVs. The results of this work are described in Project Deliverable D3.3: Results of BDFT modelling for controlling a PAV.
Ph.D. Project: Measuring, modeling and mitigating biodynamic feedthrough
Duration: February 2010 - March 2014
Vehicle accelerations affect the human body in various ways. In some cases, accelerations cause involuntary motions of limbs like arms and hands. If someone is engaged in a manual control task at the same time, these involuntary limb motions can lead to involuntary control forces and control inputs. This phenomenon is called biodynamic feedthrough (BDFT).
The control of many different vehicles is known to be vulnerable to BDFT effects, such as that of helicopters, aircraft, electric wheelchairs and hydraulic excavators. It is also known that BDFT dynamics depend on vehicle dynamics and control device dynamics, but also on factors such as seating dynamics, disturbance direction, disturbance frequency and the presence of seat belts and arm rests. The most complex and influential factor in BDFT is the human body. It is through the human body dynamics that the vehicle accelerations are transferred into involuntary limb motions and, consequently, into involuntary control inputs. Human body dynamics vary between persons with different body sizes and weights, but also within one person over time. This renders BDFT a variable dynamical relationship, not only varying between different persons (between-subject variability), but also within one person over time (within-subject variability).
The goal of the research was to increase the understanding of BDFT to allow for effective and efficient mitigation of the BDFT problem. The work dealt with several aspects of biodynamic feedthrough, but focused on the influence of the variable neuromuscular dynamics on BDFT dynamics. The research approach consisted of three parts: first, a method was developed to accurately measure BDFT. Then, several BDFT models were developed that describe the BDFT phenomenon. Finally, using the insights from the previous steps, a novel approach to BDFT mitigation was proposed.
The result of the first phase was a measurement method, capable of accurately and simultaneously measuring BDFT and neuromuscular admittance (a measure of the neuromuscular dynamics of the human arm). Based on validation experiments, it was concluded that there exists a strong dependency of BDFT dynamics on neuromuscular admittance. Furthermore, a comprehensive set of definitions, nomenclature and mathematical notations was developed. This framework for BDFT analysis provides a common ground to study, discuss and understand BDFT and its related problems.
The first results of the second phase was a physical BDFT model, which models the physical occurrence of BDFT. The model serves primarily the purpose of increasing the understanding of the relationship between neuromuscular admittance and biodynamic feedthrough. Also, a mathematical BDFT model was developed. The mathematical model is easier to implement and use than its physical counterpart. Both models have shown to be highly accurate.
In the third phase possible BDFT mitigation approaches were identified. The mitigation effectiveness of a widely-used hardware component was experimentally studied: an armrest. The results show that an armrest is an effective tool in mitigating biodynamic feedthrough. Finally, a novel approach to BDFT mitigation was proposed and validated: admittance-adaptive model-based signal cancellation. What differentiates this approach from other approaches is that it accounts for adaptations in the neuromuscular dynamics of the human body. The approach was tested, as proof-of-concept, in an experiment. Results show that the cancellation approach was successful and largely removed the negative effects of BDFT on the control effort and control performance.
Figure 2: Biodynamic feedthrough (BDFT) occurs when vehicle accelerations feed through the human body, causing involuntary control forces and involuntary control inputs (indicated in blue). One way of mitigating BDFT is to use a BDFT controller that models and cancels the involuntary inputs (indicated in red).
Joost Venrooij is project leader of the Motion Perception and Simulation research group and the Cybernetics Approach to Perception and Action research group at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany. His research interests include motion perception, motion cueing, biodynamic interferences, neuromuscular modeling, and haptics.
Full CV available upon request.
|Since July '15||Project leader of the Cybernetics Approach to Perception and Action research group at Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany|
|Since April '13||
Project leader of the Motion Perception and Simulation research group at Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany
|Dec '10 - Mar '14
Ph.D. Candidate at Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany (in co-operation with Delft University of Technology)
|Feb '10 - Mar '14||
Ph.D. Candidate at Delft University of Technology, Delft, The Netherlands (in co-operation with Max-Planck-Institute for Biological Cybernetics)
Thesis title: Measuring, modeling and mitigating biodynamic feedthrough
|Sep '06 - Aug '09||
Master of Science (M.Sc.) in Aerospace Engineering, Delft University of Technology, Delft, The Netherlands.
Thesis title: Relating biodynamic feedthrough to neuromuscular admittance
|Sep '02 - Aug '06||Bachelor of Science (B.Sc.) in Aerospace Engineering , Delft University of Technology, Delft, The Netherlands.|
|Nov '09 - Jan '10||
Research employee at Entropy Control Inc., La Jolla (San Diego), California, USA.
I worked on an independent research project about internal modeling in car driving tasks, for which I designed, executed, and analyzed various driving experiments. I investigated how drivers build a mental representation of steering dynamics, and what the impact of varying steering dynamics is on control performance.
|Dec '07 - May '08||
Research Internship at Eurocopter GmbH , Ottobrunn, Germany.
I worked in the Dynamics and Vibrations department, where I investigated the employment of trailing edge flaps to reduce pitch link forces.
|Sep '07 - Nov '07||
Research Internship at Entropy Control Inc., La Jolla (San Diego), California, USA.
I worked on haptic feedback systems and autonomous curve negotiation. The controller that I developed used various visual cues to mimic human steering behavior. Furthermore, I was responsible for setting up a fixed-base driving simulator with hardware provided by Nissan Motor Co., Ltd.
Honors and awards
|Dec '14||Winner of the Best Dissertation Award 2014 from the Max-Planck-Institut für biologische Kybernetik and Förderverein für neurowissenschaftliche Forschung e.V. This award is yearly awarded for the best Ph.D. dissertation of the Max Planck Institute for Biological Cybernetics.
|Mar '14||Received Ph.D. degree cum laude (German equivalent: summa cum laude), which is the highest distinction.
Nominated for best paper award at the 38th European Rotorcraft Forum
Paper: A practical biodynamic feedthrough model for helicopters
|Sep '11||Among the first students appearing on the TU Delft Wall of Fame, which features students of Delft University of Technology with exceptional achievements during or after their studies.
Best Student Paper Award at the IEEE International Conference on Systems, Man, and Cybernetics, for the best student paper and oral presentation.
Paper: Biodynamic feedthrough is task dependent
NVvL award for best aeronautical M.Sc. thesis awarded by the Netherlands Association of Aeronautical Engineers.
Thesis: Relating biodynamic feedthrough to neuromuscular admittance
|Aug '09||Received M.Sc. degree cum laude (German equivalent: summa cum laude), which is the highest distinction.|